Navigating the Future:
AI-ML workshop for Pharma, Chemistry, Ayurveda, and Healthcare

[Recorded] click here to Watch on Youtube

Discover the future of Pharma, Chemistry, Ayurveda, and Healthcare through the lens of Artificial Intelligence and Machine Learning.

Areas Covered

  • 🧠 Explore Cutting-edge AI Applications: Gain insights into how AI and ML are revolutionizing Pharma, Chemistry, Ayurveda, and Healthcare practices.

  • 🎙️ Learn from a Visionary: Our esteemed speaker, Mr. Kushal Sharma, Founder of Indeed Inspiring Infotech, will share his expertise and industry knowledge.

  • 🌱 Bridge Traditional Wisdom with Modern Tech: Discover the synergy between ancient Ayurvedic practices and modern technological advancements.

  • 📊 Unlock Opportunities: Understand the potential of AI and ML in optimizing drug discovery, treatment strategies, and patient care.

  • 🌐 Network with fellow job seekers and expand your opportunities

Webinar Poster

List of Contents

  • 1. Introduction to AI and Machine Learning (AIML): An overview of what AIML is and its significance in the fields of Pharma, Chemistry, Ayurveda, and Healthcare.

  • 2. Applications of AIML in Healthcare: Use cases where AIML technologies have made an impact in healthcare, such as disease diagnosis, drug discovery, and patient care.

  • 3. AIML in Pharmaceutical Research: Explore how AIML is revolutionizing drug discovery, optimizing clinical trials, and improving the development of pharmaceutical products.

  • 4. AIML in Chemistry: How AIML techniques are being applied in chemical research, including molecular modeling, compound screening, and material discovery.

  • 5. Integration of Ayurveda and AIML: Explore how AI and machine learning can be used to analyze and modernize Ayurvedic practices, including herbal medicine recommendations and patient wellness.

  • 6. Data Collection and Preprocessing: Explain the importance of high-quality data in AIML projects and discuss strategies for data collection and preprocessing, especially in healthcare and pharmaceutical contexts.

  • 7. Machine Learning Algorithms: An overview of popular machine learning algorithms and their suitability for different tasks in Pharma, Chemistry, Ayurveda, and Healthcare.

  • 8. Ethical and Regulatory Considerations: Ethical implications of AIML in healthcare and pharmaceuticals, including patient privacy, bias, and compliance with regulations.

  • 10. Hands-On Workshops and Case Studies: Opportunity to work on hands-on exercises and analyze real-world case studies related to AIML in Pharma, Chemistry, Ayurveda, and Healthcare.

  • 11. Future Trends and Challenges: Discuss emerging trends in AIML and the potential challenges that researchers and practitioners may face in these industries.

  • 12. Networking and Collaboration: Encourage participants to network, share insights, and explore potential collaborations with others in the workshop.

  • 13. Q&A Sessions: Time for participants to ask questions and seek clarification on the workshop content.